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dsyoon
2022-09-12 15:29:10 +09:00
parent 8541a1c034
commit 6690a5b022
2 changed files with 87 additions and 33 deletions
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19
Simulation.py
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@@ -97,6 +97,12 @@ class Simulation (HTS):
volume_line = go.Scatter(x=data['date'], y=data["volume"], mode='lines', name='volume')
#fast_k_line = go.Scatter(x=hts['date'], y=hts["fast_k"], mode='lines', name='fast_k')
disparity_avg5 = go.Scatter(x=data['date'], y=data["disparity_avg5"], name="disparity_avg5", line_color='#8F8203')
disparity_avg10 = go.Scatter(x=data['date'], y=data["disparity_avg10"], name="disparity_avg10", line_color='#089B5B')
disparity_avg20 = go.Scatter(x=data['date'], y=data["disparity_avg20"], name="disparity_avg20", line_color='#ff00ff')
disparity_avg60 = go.Scatter(x=data['date'], y=data["disparity_avg60"], name="disparity_avg60", line_color='#1469F4')
disparity_avg120 = go.Scatter(x=data['date'], y=data["disparity_avg120"], name="disparity_avg120", line_color='#000000')
macd_line = go.Scatter(x=data['date'], y=data["macd"], mode='lines', name='macd')
macd_s_line = go.Scatter(x=data['date'], y=data["macds"], mode='lines', name='macds')
macd_o_line = go.Scatter(x=data['date'], y=data["macdo"], mode='lines', name='macdo')
@@ -109,6 +115,7 @@ class Simulation (HTS):
candle_data = [candle_stick, upper, lower, avg3, avg6, avg9, avg12, avg20, buy_check, sell_check, laggingSpan, changeLine, baseLine]
volume_data = [volume_line]
disparity_data = [disparity_avg5, disparity_avg10, disparity_avg20, disparity_avg60, disparity_avg120]
macd_data = [macd_line, macd_s_line, macd_o_line]
stochastic_data = [slow_k_line, slow_d_line]
rsi_data = [rsi_line, rsis_line]
@@ -120,17 +127,21 @@ class Simulation (HTS):
fig.show()
"""
fig = subplots.make_subplots(rows=5, cols=1, subplot_titles=('캔들', "거래량", "MACD", "스토캐스틱", "RSI"))
fig = subplots.make_subplots(rows=6, cols=1,
subplot_titles=('캔들', "거래량", "이격도", "MACD", "스토캐스틱", "RSI"),
row_heights=[1200, 500, 500, 500, 500, 500])
for trace in candle_data:
fig.append_trace(trace, 1, 1)
for trace in volume_data:
fig.append_trace(trace, 2, 1)
for trace in macd_data:
for trace in disparity_data:
fig.append_trace(trace, 3, 1)
for trace in stochastic_data:
for trace in macd_data:
fig.append_trace(trace, 4, 1)
for trace in rsi_data:
for trace in stochastic_data:
fig.append_trace(trace, 5, 1)
for trace in rsi_data:
fig.append_trace(trace, 6, 1)
#fig.update_xaxes(nticks=5)
#fig.update_layout(height=1800, title=stock_code + "_" + given_day, xaxis_rangeslider_visible=False)

101
stock/analysis/AnalyzerSqlite.py
View File

@@ -21,6 +21,7 @@ from stock.analysis.Stochastic import Stochastic
from stock.analysis.BolingerBand import BolingerBand
from stock.analysis.IchimokuCloud import IchimokuCloud
from stock.analysis.RSI import RSI
from stock.analysis.MACD import MACD
from stock.crawler.MovingAverage import MovingAverage
class AnalyzerSqlite:
@@ -30,6 +31,7 @@ class AnalyzerSqlite:
bolingerBand = None
ichimokuCloud = None
rsi = None
macd = None
topCompany = None
fnguide = None
@@ -50,6 +52,7 @@ class AnalyzerSqlite:
self.bolingerBand = BolingerBand()
self.ichimokuCloud = IchimokuCloud()
self.rsi = RSI()
self.macd = MACD()
self.topCompany = self.getTopCompany(stockFileName, 2000)
self.fnguide = self.readFnguide(stockFileName)
@@ -132,6 +135,14 @@ class AnalyzerSqlite:
avg120 = list(reversed(stock['avg120']))
avg240 = list(reversed(stock['avg240']))
avg300 = list(reversed(stock['avg300']))
disparity_avg5 = list(reversed(stock['disparity_avg5']))
disparity_avg10 = list(reversed(stock['disparity_avg10']))
disparity_avg20 = list(reversed(stock['disparity_avg20']))
disparity_avg60 = list(reversed(stock['disparity_avg60']))
disparity_avg120 = list(reversed(stock['disparity_avg120']))
macd = list(reversed(stock['macd']))
macdo = list(reversed(stock['macdo']))
macds = list(reversed(stock['macds']))
rsi = list(reversed(stock['rsi']))
rsis = list(reversed(stock['rsis']))
stochastic_slow_k = list(reversed(stock['stochastic_slow_k']))
@@ -168,6 +179,19 @@ class AnalyzerSqlite:
volume = go.Bar(x=ymd, y=volume, name="volume")
volume_data = [volume]
disparity_avg5 = go.Scatter(x=ymd, y=disparity_avg5, name="disparity_avg5", line_color='#8F8203')
disparity_avg10 = go.Scatter(x=ymd, y=disparity_avg10, name="disparity_avg10", line_color='#089B5B')
disparity_avg20 = go.Scatter(x=ymd, y=disparity_avg20, name="disparity_avg20", line_color='#ff00ff')
disparity_avg60 = go.Scatter(x=ymd, y=disparity_avg60, name="disparity_avg60", line_color='#1469F4')
disparity_avg120 = go.Scatter(x=ymd, y=disparity_avg120, name="disparity_avg120", line_color='#000000')
disparity_data = [disparity_avg5, disparity_avg10, disparity_avg20, disparity_avg60, disparity_avg120]
# macd
macd_line = go.Scatter(x=ymd, y=macd, mode='lines', name='macd')
macd_s_line = go.Scatter(x=ymd, y=macds, mode='lines', name='macds')
macd_o_line = go.Scatter(x=ymd, y=macdo, mode='lines', name='macdo')
macd_data = [macd_line, macd_s_line, macd_o_line]
# stochastic
rsi = go.Scatter(x=ymd, y=rsi, name="rsi", line_color='#8B4513')
rsis = go.Scatter(x=ymd, y=rsis, name="rsis", line_color='#4169E1')
@@ -178,18 +202,21 @@ class AnalyzerSqlite:
slow_d = go.Scatter(x=ymd, y=stochastic_slow_d, name="Slow%D", line_color='#4169E1')
stochastic_data = [slow_k, slow_d]
fig = subplots.make_subplots(rows=4, cols=1,
subplot_titles=('차트', '거래량', 'rsi', 'Stochastic'),
row_heights=[1200, 500, 500, 500])
fig = subplots.make_subplots(rows=6, cols=1,
subplot_titles=('캔들', "거래량", "이격도", "MACD", "스토캐스틱", "RSI"),
row_heights=[1200, 500, 500, 500, 500, 500])
for trace in candle_data:
fig.append_trace(trace, 1, 1)
for trace in volume_data:
fig.append_trace(trace, 2, 1)
for trace in rsi_data:
for trace in disparity_data:
fig.append_trace(trace, 3, 1)
for trace in stochastic_data:
for trace in macd_data:
fig.append_trace(trace, 4, 1)
for trace in stochastic_data:
fig.append_trace(trace, 5, 1)
for trace in rsi_data:
fig.append_trace(trace, 6, 1)
fig.update_layout(height=2200, xaxis_rangeslider_visible=False)
@@ -305,11 +332,13 @@ class AnalyzerSqlite:
sql = 'SELECT ymd, close, open, high, low, volume, '
sql += ' avg3, avg4, avg5, avg6, avg10, avg12, avg20, avg36, avg40, avg48, avg60, avg120, avg200, avg240, avg300, '
sql += ' disparity_avg5, disparity_avg10, disparity_avg20, disparity_avg60, disparity_avg120, '
sql += ' bolingerband_upper, bolingerband_lower, bolingerband_middle, '
sql += ' ichimokucloud_changeLine, ichimokucloud_baseLine, ichimokucloud_leadingSpan1, ichimokucloud_leadingSpan2, '
sql += ' stochastic_fast_k, stochastic_slow_k, stochastic_slow_d, '
sql += ' rsi, rsis '
sql += ' FROM ' + TableName + ' where CODE=? order by ymd desc limit 512'
sql += ' rsi, rsis, '
sql += ' macd, macds, macdo '
sql += ' FROM ' + TableName + ' where CODE=? order by ymd desc limit 512 '
cursor.execute(sql, (CODE,))
prices = cursor.fetchall()
@@ -319,10 +348,12 @@ class AnalyzerSqlite:
ymd = []
close, open, high, low, volume = [], [], [], [], []
avg3, avg4, avg5, avg6, avg10, avg12, avg20, avg36, avg40, avg48, avg60, avg120, avg200, avg240, avg300 = [], [], [], [], [], [], [], [], [], [], [], [], [], [], []
disparity_avg5, disparity_avg10, disparity_avg20, disparity_avg60, disparity_avg120 = [], [], [], [], []
bolingerband_upper, bolingerband_lower, bolingerband_middle = [], [], []
ichimokucloud_changeLine, ichimokucloud_baseLine, ichimokucloud_leadingSpan1, ichimokucloud_leadingSpan2 = [], [], [], []
stochastic_fast_k, stochastic_slow_k, stochastic_slow_d = [], [], []
rsi, rsis = [], []
macd, macds, macdo = [], [], []
for price in prices:
ymd.append(price[0])
@@ -346,31 +377,40 @@ class AnalyzerSqlite:
avg200.append(price[18])
avg240.append(price[19])
avg300.append(price[20])
bolingerband_upper.append(price[21])
bolingerband_lower.append(price[22])
bolingerband_middle.append(price[23])
ichimokucloud_changeLine.append(price[24])
ichimokucloud_baseLine.append(price[25])
ichimokucloud_leadingSpan1.append(price[26])
ichimokucloud_leadingSpan2.append(price[27])
stochastic_fast_k.append(price[28])
stochastic_slow_k.append(price[29])
stochastic_slow_d.append(price[30])
rsi.append(price[31])
rsis.append(price[32])
disparity_avg5.append(price[21])
disparity_avg10.append(price[22])
disparity_avg20.append(price[23])
disparity_avg60.append(price[24])
disparity_avg120.append(price[25])
bolingerband_upper.append(price[26])
bolingerband_lower.append(price[27])
bolingerband_middle.append(price[28])
ichimokucloud_changeLine.append(price[29])
ichimokucloud_baseLine.append(price[30])
ichimokucloud_leadingSpan1.append(price[31])
ichimokucloud_leadingSpan2.append(price[32])
stochastic_fast_k.append(price[33])
stochastic_slow_k.append(price[34])
stochastic_slow_d.append(price[35])
rsi.append(price[36])
rsis.append(price[37])
macd.append(price[38])
macds.append(price[39])
macdo.append(price[40])
stock = {
"ymd": ymd,
"close": close, "open": open, "high": high, "low": low, "volume": volume,
"avg3": avg3, "avg4": avg4, "avg5": avg5, "avg6": avg6, "avg10": avg10, "avg12": avg12, "avg20": avg20, "avg36": avg36, "avg40": avg40, "avg48": avg48, "avg60": avg60, "avg120": avg120, "avg200": avg200, "avg300": avg300,
"avg240": avg240,
"avg3": avg3, "avg4": avg4, "avg5": avg5, "avg6": avg6, "avg10": avg10, "avg12": avg12, "avg20": avg20, "avg36": avg36, "avg40": avg40, "avg48": avg48, "avg60": avg60, "avg120": avg120, "avg200": avg200, "avg240": avg240, "avg300": avg300,
"disparity_avg5": disparity_avg5, "disparity_avg10": disparity_avg10, "disparity_avg20": disparity_avg20, "disparity_avg60": disparity_avg60, "disparity_avg120": disparity_avg120,
"bolingerband_upper": bolingerband_upper, "bolingerband_lower": bolingerband_lower,
"bolingerband_middle": bolingerband_middle,
"ichimokucloud_changeLine": ichimokucloud_changeLine, "ichimokucloud_baseLine": ichimokucloud_baseLine,
"ichimokucloud_leadingSpan1": ichimokucloud_leadingSpan1,
"ichimokucloud_leadingSpan2": ichimokucloud_leadingSpan2,
"stochastic_fast_k": stochastic_fast_k, "stochastic_slow_k": stochastic_slow_k, "stochastic_slow_d": stochastic_slow_d,
"rsi": rsi, "rsis": rsis
"rsi": rsi, "rsis": rsis,
"macd": macd, "macds": macds, "macdo": macdo
}
return stock
@@ -744,6 +784,7 @@ class AnalyzerSqlite:
self.stochastic.analyze(stock)
self.bolingerBand.analyze(stock)
self.rsi.analyze(stock)
self.macd.analyze(stock)
sorted_stock = sorted(stock["PRICE"], key=lambda x: x['ymd'], reverse=True)
for price in sorted_stock:
@@ -756,8 +797,8 @@ class AnalyzerSqlite:
sql += " bolingerband_upper, bolingerband_lower, bolingerband_middle, "
sql += " ichimokucloud_changeLine, ichimokucloud_baseLine, ichimokucloud_leadingSpan1, ichimokucloud_leadingSpan2, "
sql += " stochastic_fast_k, stochastic_slow_k, stochastic_slow_d, "
sql += " rsi, rsis) "
sql += " VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)"
sql += " rsi, rsis, macd, macds, macdo) "
sql += " VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)"
cursor.execute(sql, (
stock["CODE"], stock["NAME"], price['ymd'], price['close'], price['diff'], price['open'], price['high'], price['low'], price['volume'],
@@ -767,7 +808,7 @@ class AnalyzerSqlite:
price['ichimokucloud_changeLine'], price['ichimokucloud_baseLine'], price['ichimokucloud_leadingSpan1'],
price['ichimokucloud_leadingSpan2'],
price['stochastic_fast_k'], price['stochastic_slow_k'], price['stochastic_slow_d'],
price['rsi'], price['rsis'],))
price['rsi'], price['rsis'], price['macd'], price['macds'], price['macdo'],))
else:
sql = "UPDATE " + stockAnalysisTableName + " SET close=?, diff=?, open=?, high=?, low=?, volume=?, "
@@ -777,6 +818,7 @@ class AnalyzerSqlite:
sql += " ichimokucloud_changeLine=?, ichimokucloud_baseLine=?, ichimokucloud_leadingSpan1=?, ichimokucloud_leadingSpan2=?, "
sql += " stochastic_fast_k=?, stochastic_slow_k=?, stochastic_slow_d=?, "
sql += " rsi=?, rsis=? "
sql += " macd=?, macds=?, macdo=? "
sql += " WHERE CODE=? and ymd=?"
cursor.execute(sql,
@@ -787,6 +829,7 @@ class AnalyzerSqlite:
price['ichimokucloud_leadingSpan1'], price['ichimokucloud_leadingSpan2'],
price['stochastic_fast_k'], price['stochastic_slow_k'], price['stochastic_slow_d'],
price['rsi'], price['rsis'],
price['macd'], price['macds'], price['macdo'],
stock["CODE"], price['ymd'],))
break
@@ -960,9 +1003,9 @@ if __name__ == "__main__":
stockFileName = PROJECT_HOME + '/resources/stock.db'
analyzer = AnalyzerSqlite(PROJECT_HOME, stockFileName)
analyzer.analyzeDaily()
analyzer.analyzeGrouping("weekly")
analyzer.analyzeGrouping("monthly")
#analyzer.analyzeDaily()
#analyzer.analyzeGrouping("weekly")
#analyzer.analyzeGrouping("monthly")
# HTML 출력
outPath = os.path.join(PROJECT_HOME, "resources", "analysis")